Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
Most of these occupations require a four-year bachelor's degree, but some do not.
Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.
Detailed Work Activities
Analyze data to inform operational decisions or activities.
Analyze business or financial data.
Determine appropriate methods for data analysis.
Prepare data for analysis.
Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.
Prepare graphics or other visual representations of information.
Prepare analytical reports.
Present research results to others.
Develop procedures to evaluate organizational activities.
Select resources needed to accomplish tasks.
Analyze data to identify trends or relationships among variables.
Analyze data to identify or resolve operational problems.
Update technical knowledge.
Advise others on analytical techniques.
Develop scientific or mathematical models.
Write computer programming code.
Tasks
Analyze, manipulate, or process large sets of data using statistical software.
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
Clean and manipulate raw data using statistical software.
Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
Design surveys, opinion polls, or other instruments to collect data.
Identify business problems or management objectives that can be addressed through data analysis.
Identify relationships and trends or any factors that could affect the results of research.
Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
Recommend data-driven solutions to key stakeholders.
Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
Write new functions or applications in programming languages to conduct analyses.
Data Source: This page includes information from the O*NET 28.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. This page includes Employment Projections program, Occupational Employment and Wage Statistics program, U.S. Bureau of Labor Statistics.
